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\begin{document}

\title{Selecting suitable climate models for examining future changes in soil
erosion and muddy flooding}



\author[1]{Neil Brannigan}%
\author[1]{Donal Mullan}%
\author[2]{Karel Vandaele}%
\author[1]{Conor Graham}%
\author[1]{Jennifer  McKinley}%
\author[3]{John Meneely}%
\affil[1]{Queen's University Belfast}%
\affil[2]{Watering van Sint-Truiden}%
\affil[3]{Queen’s University Belfast}%


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  \date{June 14, 2024}


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\begin{abstract}
Climate models consistently project large increases in the frequency and
magnitude of extreme precipitation events in the 21st century, revealing
the potential for widespread impacts on various aspects of society.
While the impacts on flooding receive particular attention, there is
also considerable damage and associated cost for other
precipitation--driven phenomena, including soil erosion and muddy
flooding. Multiple studies have shown that climate change will worsen
the impacts of soil erosion and muddy flooding in various regions. These
studies typically drive erosion models with output from a single climate
model or a few models with little justification. A blind approach to
climate model selection increases the risk of simulating a narrower
range of possible scenarios, limiting vital information for mitigation
planning and adaptation. This study provides a comprehensive methodology
to efficiently select suitable climate models for simulating soil
erosion and muddy flooding. For a study region in Belgium using the WEPP
soil erosion model, we compare the performance of our novel methodology
against other model selection methods for a future period (2081--2100).
The main findings reveal that our methodology is successful in
generating the widest range of future scenarios from a small number of
models, compared with other selection methods. This represents a novel
targeted approach to climate model selection with respect to soil
erosion by water but could be modified for other precipitation--driven
impact sectors. This will ensure a broad range of climate impacts are
simulated so the best- and worst-case scenarios can be adequately
prepared for.%
\end{abstract}%



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